Biomedical subjects

Catherine Nguyen

Publications and source records attributed to Catherine Nguyen.

29 records · Page 2Linked to original sources

PubMed2003

Gene expression profiling of multiple myeloma reveals molecular portraits in relation to the pathogenesis of the disease.

Although multiple myeloma (MM) is a unique entity, a marked heterogeneity is actually observed among the patients, which has been first related to immunoglobulin (Ig) types and light chain subtypes and more recently to chromosomal abnormalities. To further investigate this genetic heterogeneity, we analyzed gene expression profiles of 92 primary tumors according to their Ig types and light chain subtypes with DNA microarrays. Several clusters of genes involved in various biologic functions such as immune response, cell cycle control, signaling, apoptosis, cell adhesion, and structure significantly discriminated IgA- from IgG-MM. Genes associated with inhibition of differentiation and apoptosis induction were up-regulated while genes associated with immune response, cell cycle control, and apoptosis were down-regulated in IgA-MM. According to the expression of the 61 most discriminating genes, BJ-MM represented a separate subgroup that did not express either the genes characteristic of IgG-MM or those of IgA-MM at a high level. This suggests that transcriptional programs associated to the switch could be maintained up to plasma cell differentiation. Several genes whose products are known to stimulate bone remodeling discriminate between kappa- and lambda-MM. One of these genes, Mip-1alpha, was overexpressed in the kappa subgroup. In addition, we established a strong association (P =.0001) between kappa subgroup expressing high levels of Mip-1alpha and active myeloma bone disease. This study shows that DNA microarrays enable us to perform a molecular dissection of the bioclinical diversity of MM and provide new molecular tools to investigate the pathogenesis of malignant plasma cells.

Adult↗

PubMed2003

Spatial, a new nuclear factor tightly regulated during mouse spermatogenesis.

In order to clarify general mechanisms of T cell development, we used array technology to identify genes differentially expressed between wild type and mutant mice thymuses. This quantitative differential screening leads to the isolation of Spatial, a putative transcription factor, expressed at high level in thymic cortical stromal cells. We report here, by RT-PCR on 48 distinct tissues that Spatial is also highly expressed in testis. Interestingly, the testicular expression is developmentally regulated, since it only appears in adult mice around 7-8 weeks of age. Analysis of purified testicular cell types show that Spatial expression is restricted to haploid round spermatids during spermiogenesis and the expression sites were further localized by in situ hybridization to step 2-10 spermatids. Thus, this recently described nuclear factor constitutes a new marker of the round spermatid stage that may play a key role in the control of male germ cell development.

Animals↗

PubMed2003

Gene expression profiling during thymus ontogeny and its association with TCRVbeta8.1-Dbeta2.1 rearrangements of inbred mouse strains.

The V(D)J recombination of TCRalpha and beta in early developing T-cells is a highly modulated phenomenon initiated and completed by recombinase complex (RAG-1 and RAG-2), and regulated by other gene products such as interleukins. To further evaluate the association of several other gene products with the evolution of TCRVbeta8.1 V(D)J rearrangements in vivo, the mRNA expression levels of seven interleukins, three cytokines, receptors TCRVbeta8.1 and IL-2Rbeta, MHC-I/MHC-II, RAG-1/ RAG-2 and retroviral superantigen MMTV(SW) were measured by RT-PCR during the fetal development of the thymus of three inbred mouse strains (Balb-c, C57B1/6 and CBA/J). Clustering using the Tree View software, was used to organize these genes based on similarity of expression patterns. Each strain displayed a different expression profile during thymus ontogeny. During the late developmental stage the most evident association was the kinetics of MMTV(SW) retrovirus, IL-2Rbeta and IL-7 overexpression with reduction of TCRVbeta8.1-D1beta2.1 rearrangement in the thymus of CBA/J mice. These data suggest a susceptibility of this strain to expression of MMTV(SW) upon reduction of the rearranged TCRVbeta8.1-Dbeta2.1 segment in developing thymocytes, with parallel IL-7 overexpression.

Animals↗

PubMed2003

DNA arrays in clinical oncology: promises and challenges.

Cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. Current diagnostic and prognostic classifications, based on clinical and pathologic factors, are insufficient to reflect the whole clinical heterogeneity of tumors. Most current anticancer agents do not differentiate between cancerous and normal cells, leading sometimes to disastrous adverse effects. Recent advances in human genome research and high-throughput molecular technologies make it possible finally to tackle the molecular complexity of malignant tumors. With DNA array technology, mRNA expression levels of thousands of genes can be measured simultaneously in a single assay. Oncology is benefiting on multiple fronts. Gene expression profiles are revealing new biologically and clinically relevant tumor subclasses previously indistinguishable and are identifying new diagnostic and prognostic biomarkers as well as new potential therapeutic targets. Here, we review the technology and present clinical applications for which promising results have been obtained. Finally, we discuss issues that must be resolved in the near future to allow DNA arrays to translate into benefits for cancer patients.

Gene Expression Profiling↗

PubMed2002

Expression profiling in mouse fetal thymus reveals clusters of coordinately expressed genes that mark individual stages of T-cell ontogeny.

To search for genes that participate in regulatory networks sustaining mouse embryonic T-cell development, we have performed expression profiling using nylon macroarrays. Labeled samples representative of individual developmental stages were utilized, taking advantage of cell homogeneity during early thymus ontogeny. cDNAs revealing differential expression were further selected using labeled samples derived from lymphoid versus non-lymphoid tissues, and from mutant thymi exhibiting T-cell developmental defects. We thus identified clusters of coexpressed genes during T-cell embryogenesis and characterized their sequences through bioinformatics. We compare our results with those from other profiling analyses in the immune system, and discuss their implications for the definition of genes whose products are involved in T-cell development.

Animals↗

PubMed2002

Gene expression profiling defines molecular subtypes of classical Hodgkin's disease.

Although the prognosis of Hodgkin's disease is relatively good, around 20% of patients do not benefit from current therapies and succumb to their disease. A large-scale molecular characterization of disease might help improve HD management. Using cDNA arrays, we studied the mRNA expression levels of approximately 1000 selected genes in 34 benign and malignant lymphoid samples including 21 classical Hodgkin's disease (HD) tissue samples. Hierarchical clustering identified three main molecular groups of HD tumours relevant with respect to histology and clinical outcome (response to therapy and survival). Samples from all bad outcome HD (BOHD) patients clustered in one group whereas the two other groups contained most good outcome HD (GOHD) cases. The nodular sclerosis GOHD samples overexpressed genes involved in apoptotic induction and cell signalling, including cytokines, while the BOHD samples were characterized by the upregulation of genes involved in fibroblast activation, angiogenesis, extracellular matrix remodelling, cell proliferation, and the downregulation of tumour suppressor genes. Our results establish a molecular taxonomy of HD correlating with response to therapy and clinical outcome, thereby suggesting the possibility of improving the current prognostic classification.

Apoptosis↗

PubMed2002

Gene expression profiles of poor-prognosis primary breast cancer correlate with survival.

The extensive heterogeneity of breast cancer complicates the precise assessment of tumour aggressiveness, making therapeutic decisions difficult and treatments inappropriate in some cases. Consequently, the long-term metastasis-free survival rate of patients receiving adjuvant chemotherapy is only 60%. There is a genuine need to identify parameters that might accurately predict the effectiveness of this treatment for each patient. Using cDNA arrays, we profiled tumour samples from 55 women with poor-prognosis breast cancer treated with adjuvant anthracycline-based chemotherapy. Gene expression monitoring was applied to a set of about 1000 candidate cancer genes. Differences in expression profiles provided molecular evidence of the clinical heterogeneity of disease. First, we confirmed the capacity of a 23-gene predictor set, identified in a previous study, to distinguish between tumours associated with different survival. Second, using a refined gene set derived from the previous one, we distinguished, among the 55 clinically homogeneous tumours, three classes with significantly different clinical outcome: 5-year overall survival and metastasis-free survival rates were respectively 100% and 75% in the first class, 65% and 56% in the second and 40% and 20% in the third. This discrimination resulted from the differential expression of two clusters of genes encoding proteins with diverse functions, including the estrogen receptor (ER). Another finding was the identification of two ER-positive tumour subgroups with different survival. These results indicate that gene expression profiling can predict clinical outcome and lead to a more precise classification of breast tumours. Furthermore, the characterization of discriminator genes might accelerate the development of new specific and alternative therapies, allowing more rationally tailored treatments that are potentially more efficient and less toxic.

Breast Neoplasms↗

PubMed2002

Distinct and complementary information provided by use of tissue and DNA microarrays in the study of breast tumor markers.

Emerging high-throughput screening technologies are rapidly providing opportunities to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. Currently, cDNA arrays allow the quantitative measurement of thousands of mRNA expression levels simultaneously. Validation of this tool in hospital settings can be done on large series of archival paraffin-embedded tumor samples using the new technique of tissue microarray. On a series of 55 clinically and pathologically homogeneous breast tumors, we compared for 15 molecules with a proven or suspected role in breast cancer, the mRNA expression levels measured by cDNA array analysis with protein expression levels obtained using tumor tissue microarrays. The validity of cDNA array and tissue microarray data were first verified by comparison with quantitative reverse transcriptase-polymerase chain reaction measurements and immunohistochemistry on full tissue sections, respectively. We found a good correlation between cDNA and tissue array analyses in one-third of the 15 molecules, and no correlation in the remaining two-thirds. Furthermore, protein but not RNA levels may have prognostic value; this was the case for MUC1 protein, which was studied further using a tissue microarray containing approximately 600 tumor samples. For THBS1 the opposite was observed because only RNA levels had prognostic value. Thus, differences extended to clinical prognostic information obtained by the two methods underlining their complementarity and the need for a global molecular analysis of tumors at both the RNA and protein levels.

Base Sequence↗

PubMed2002

Gene profiling approach to establish the molecular bases for partial versus full activation of naïve CD8 T lymphocytes.

When initial antigen encounter involves optimal antigenic and costimulatory stimuli, naïve CD8 T cells undergo a developmental program that leads to their activation, expansion and acquisition of effector functions (including production of IL-2, IFNgamma and expression of cytolytic effector molecules). A subset of the activated CD8 T cells thrives as long-lived memory cells. Encounter of tissue-associated, and in particular tumor-associated antigen, may often be suboptimal in terms of antigenicity and costimulation, however. We previously developed a model of naïve CD8 T cells from transgenic mice expressing an alloreactive TCR for which a mutant alloantigen behaved as a partial agonist, inducing only some of the effector functions induced by the native alloantigen. To ascertain the molecular bases for the establishment of divergent fates within the same naïve CD8 T cells, we have used cDNA microarrays to monitor sequential gene expression patterns in conditions of full or partial response of these naïve CD8 T cells. Of the 5000 different genes monitored on the array, 18% showed changes in expression in activated versus naïve CD8 T cells, independent of whether stimulation was with full or partial agonist. These included antigen-induced upregulated as well as downregulated genes. Clusters of genes that were differentially expressed were also identified, being either (i) weakly versus strongly, or (ii) transiently versus stably expressed in response to partial and full agonist, respectively. They included (i) genes encoding costimulatory molecules and (ii) genes controlling cytolytic function, cytokine production, and chemokines. Therefore, the cDNA microarray approach was a sensitive tool to provide an exhaustive picture of T cell activation as it could discriminate quantitative, qualitative and dynamic differences in mRNA expression profiles between fully or partially activated T cells.

Animals↗

PubMed2002

Prognosis of breast cancer and gene expression profiling using DNA arrays.

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current therapeutic strategies-based on clinicopathlogical factors-less than perfectly adapted to each patient. Today, DNA arrays, by allowing the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay, provide novel tools to tackle this complexity. Potential applications are multiple in the cancer field and the first research results are promising. Using home-made DNA arrays in an approach easily compatible with academic research-nylon support and radioactive detection-we identified a predictor set of 23 genes whose expression patterns differentiated two groups of breast cancer patients with different survival after adjuvant chemotherapy. We then validated and further extended these results in a larger, independent and homogeneous series of poor prognosis primary breast cancers treated with adjuvant anthracyclin-based chemotherapy. We confirmed the prognostic classification provided by the 23-gene set predictor. We then improved the predictor set and refined the classification by sorting the tumors into three classes with significantly different long-term survival. These results show the potential of the technology with an accessible approach for academic research teams. We also showed that nylon DNA arrays with radioactive detection are associated with excellent sensitivity, an advantage in clinical situations where the amount of available material is limited.

Breast Neoplasms↗

PubMedDate not supplied

Gene expression profiling of breast carcinomas using nylon DNA arrays.

Clinically very heterogeneous, breast cancer prognosis and treatment response are difficult to predict with the current prognostic histoclinical parameters. Mammary oncogenesis remains poorly understood. DNA array technology allows the simultaneous analysis of the mRNA expression levels of thousands of genes in biological samples. Applied to breast tumours, expression profiles will boost our knowledge of oncogenesis, will offer new potential therapeutic targets and new prognostic and predictive markers. Today, the most accessible approach for academic research teams is that of Nylon DNA arrays with radioactive detection, which in addition allows profiling of small clinical samples.

Breast Neoplasms↗